The hazards of helping: Work, mission and risk in non-profit social service organizations
Bibliographic record
Abstract
Abstract Non-profit organizations play an important role in the provision of health and social services. No longer temporary providers of emergency services, non-profit organizations appear to be permanent features of the social service landscape. Despite some of the intrinsic rewards that work in non-profit organizations offers, jobs in these organizations can be characterized by high demands, long working hours, low pay and exposure to violence and infectious disease, conditions which may be deleterious to worker health. This paper is based on an ethnography of three non-profit organizations: a homeless women's drop in, a drug treatment agency and a men's homeless shelter. We examine organizational 'mission,' a dominant discourse about the purpose and value of providing 'help' to marginalized clients, and the implications it has for work practices and for the way that workers understand work-related risk in these organizations. We describe how the notion of mission is continually reproduced, and trace its relationship to worker risk acceptance and risk taking. We suggest that the functions of such discursive commitments in organizations, and their implications for the well-being of workers, underscores the importance of understanding organizational culture and the social construction of risk when attempting to improve working conditions and protect worker health in social service non-profit organizations. Keywords: risksocial servicesnon-profit organizationsoccupational health and safetymission Notes 1. This study was the doctoral dissertation of the first author. 2. Toronto is a large city in the province of Ontario, Canada. 3. All had at least one site located in the 'inner city.' 4. All names are pseudonyms and certain details have been changed to ensure anonymity. 5. Although each organization had a formal mission statement, most workers could not recite the formal organizational mission statement. However, they were able to talk with facility about values underlying their work, their personal beliefs and important organizational goals. Our examination of mission is primarily based on these discussions and not on the content of the formal mission statements. 6. By using the term 'discourse' we refer to a set of texts, including things like procedures, words, common understandings, which give structure to the way a certain situation, object or process is conceptualized (Cheek Citation2004). There is a dialectical relationship between these texts (or discourses) and the situations, objects or processes they frame. For example, using familial or familiar language to refer to clients (client as brother or friend) might shape organizational design. The workplace may be designed in a way that encourages socialization and free movement of clients in the organization, in turn, such configurations may encourage workers to think (and speak) of clients as family or friends. Discourse then is 'socially consequential' (Wodak Citation2004) and plays a role in constituting relationships and practices in the workplace. 7. In all quotes, the emphasis is ours.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".